Abstract
Atmospheric Radiation Measurement (ARM) is a multi-laboratory/multi-institutional, US Department of Energy Office of Science National User Facility. ARM's data is currently hosted at the ARM Data Center (ADC) in Oak Ridge, Tennessee. The ADC holds more than 12,000 data products, with a total holding of more than 1.8 PB of data that dates back to 1992. This includes data from instruments, value-added products, model outputs, field campaigns, and principle investigator contributed data. In this paper, we discuss how big federal scientific data centers, such as ARM, that use modern and scalable architecture apply findable, accessible, interoperable, and reusable (FAIR) data principles to improve overall efficiency. These principles mainly emphasize machine-to-machine interactions that are directly applicable to ARM because of its data volume.
Original language | English |
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Title of host publication | Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 |
Editors | Chaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 6033-6036 |
Number of pages | 4 |
ISBN (Electronic) | 9781728108582 |
DOIs | |
State | Published - Dec 2019 |
Event | 2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States Duration: Dec 9 2019 → Dec 12 2019 |
Publication series
Name | Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 |
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Conference
Conference | 2019 IEEE International Conference on Big Data, Big Data 2019 |
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Country/Territory | United States |
City | Los Angeles |
Period | 12/9/19 → 12/12/19 |
Funding
This research was supported by the Atmospheric Radiation Measurement (ARM) user facility, a U.S. Department of Energy (DOE) Office of Science user facility managed by the Office of Biological and Environmental Research. This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://www.energy.gov/downloads/doe-public-access-plan).
Keywords
- ARM Data Center
- Big data
- FAIR
- data management
- scientific data mining